guranshsaran/soundsense-sudormrf-separation

SoundSense AI - GroupComm SudoRM-RF Speech Separator

This is a fine-tuned/adapted model checkpoint for SoundSense AI.

Base model / source:

• —SudoRM-RF (Group Communication variant), https://github.com/etzinis/sudormrf
• —Tzinis et al., "Sudo rm -rf: Efficient networks for universal audio source separation"

Training data:

• —LibriSpeech train-clean-360 (speech) + WHAM! noise (5000 real ambient noise recordings)
• —Synthetic 2/3-speaker noisy mixtures generated on-the-fly, random SNR -5 to +20 dB

Use:

• —Part of SoundSense AI hackathon submission (Stage 2: Speech Separation).
• —Isolates up to 3 simultaneous speakers from a noisy mixed-audio input.

Limitations:

• —Built for prototype/demo use.
• —Current SI-SNR: 2.51 dB (2-speaker noisy), 0.59 dB (3-speaker noisy) — below the target KPI of >18 dB / >10 dB respectively. Separation quality is not yet sufficient for clean speaker isolation; further training required.
• —Performance should be verified on the target environment before deployment.